Further implementation of Cullen's suggestions

Author: tliddell4

R/global_variables.R

@@ -2,8 +2,31 @@
 # This is because we are referencing column names in dplyr / data.table objects which use
 # Non-Standard Evaluation.
 
-globalVariables(c("cell_area_km2", "coverage_fraction", "day", "era5_grid",
-                  "hour", "month", "minute", "poly_id", "sum_weight", "value",
-                  "w_area", "w_sum", "weight", "x", "y", "year", ".",
-                  "is_right_xmin", "is_left_xmax", "x_low", "x_high", "y_low",
-                  "y_high", "..cols_to_keep"))
+globalVariables(
+  c(
+    "cell_area_km2",
+    "coverage_fraction",
+    "day",
+    "era5_grid",
+    "hour",
+    "month",
+    "minute",
+    "poly_id",
+    "sum_weight",
+    "value",
+    "w_area",
+    "w_sum",
+    "weight",
+    "x",
+    "y",
+    "year",
+    ".",
+    "is_right_xmin",
+    "is_left_xmax",
+    "x_low",
+    "x_high",
+    "y_low",
+    "y_high",
+    "..cols_to_keep"
+  )
+)

R/staggregate.R

@@ -75,7 +75,7 @@ daily_aggregation <- function(data, overlay_weights, daily_agg, time_interval='1
   }
 
   # Check for the final case in which the polygons just span the entire globe
-  if(length(unique(weights_dt[,x] >= terra::ncol(clim_stack)))){
+  if(length(unique(weights_dt[,x])) >= terra::ncol(clim_stack)){
     polygons_split <- FALSE
   }
 
@@ -506,7 +506,7 @@ staggregate_polynomial <- function(data, overlay_weights, daily_agg, time_agg =
   layer_names <- setup_list[[2]] # Pulls the saved layer names
 
   # Polynomial transformation
-  poly_orders <- seq(1:degree) # Compute values from 1 to degree
+  poly_orders <- 1:degree # Compute values from 1 to degree
   list_length <- length(poly_orders) # How many lists are in the final object
   list_names <- sapply(1:list_length, FUN=function(x){paste("order", poly_orders[x], sep="_")})